Threshold-based Fall Detection

Threshold-Based Fall Detection is a fall detection method that belongs to the class of rule-based systems and is distinguished by its reliance on predefined physiological or kinematic thresholds—such as acceleration magnitude, angular velocity, or posture angle—to trigger fall alarms when sensor measurements exceed established limits.

47

Publications

3.7K

Citations

173

Authors

78

Institutions

Publications per year

2017–2026

20

Authors

173

  1. AB
    Alan Bourke

    University of Limerick, Ireland

    6 publications · 1.6K citations

    6

    h-index

  2. GÓ
    Gearóid ÓLaighin

    Ollscoil na Gaillimhe – University of Galway, Ireland

    3 publications · 318 citations

    3

    h-index

  3. CC
    Chia-Tai Chan

    National Yang Ming Chiao Tung University, Taiwan

    2 publications · 114 citations

    2

    h-index

  4. MK
    Maarit Kangas

    University of Oulu, Finland

    2 publications · 215 citations

    2

    h-index

  5. GL
    G.M. Lyons

    University of Limerick, Ireland

    2 publications · 1.3K citations

    2

    h-index

1–5 of 173

Venues

  1. Sensors

    4 publications · 261 citations

    4

    h-index

  2. IEEE Sensors Journal

    3 publications · 190 citations

    3

    h-index

  3. Conference proceedings

    Conference · 2 publications · 219 citations

    2

    h-index

  4. IEEE Internet of Things Journal

    2 publications · 99 citations

    2

    h-index

  5. Applied Sciences

    1 publications · 12 citations

    1

    h-index

1–5